对随机易感感染疫苗疫情模型的阳性保存数值方法和放松控制与马尔科夫切换
1School of Mathematics and Statistics, Ningxia University, Yinchuan, China.
概括
一个新的对数截断的欧勒-马鲁雅马方案改进了易受感染-接种疫苗 (SIV) 流行病模型的数值解决方案,实现了更好的疾病预测和控制策略的1次趋同.
科学领域:
- 流行病学 流行病学
- 计算数学 计算数学 计算数学
- 随机过程 随机过程
背景情况:
- 随机易感-感染-接种疫苗 (SIV) 模型对于理解传染病动态至关重要.
- 由于非线性术语,SIV模型的分析解决方案往往难以解决.
- 像欧勒-马鲁雅马 (EM) 这样的现有数值方法具有有限的收率 (1/2顺序).
研究的目的:
- 为随机SIV模型开发一种新的数值方案,以提高合性.
- 确保流行病建模的积极和稳定的数值解决方案.
- 用先进的近似方法研究传染病的最佳控制策略.
主要方法:
- 一个对数截断的欧勒-马鲁山 (EM) 方案的构建.
- 用马尔科夫切换的随机SIV模型存在一个不变度的证明.
- 马尔科夫链近似方法用于放松控制的应用.
主要成果:
- 拟议的对数缩短的EM方案实现了1次的收.
- 该方案保证了随机SIV模型的正数数值解决方案.
- 随着网格大小的减少,马尔科夫链近似方法趋于最佳的控制策略.
结论:
- 开发的对数切断EM方案对SIV建模的现有方法进行了显著改进.
- 该研究为预测疾病动态和优化干预策略提供了一个强大的框架.
- 数字示例验证了理论发现和新方案的有效性.
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